In recent years in a rapidly developing mobile communication system (the Personal Handyphone System (PHS) for example) there has been proposed a system in which when a radio base station and a mobile terminal device communicate, the radio base station employs adaptive array processing to extract a signal received from a specific, desired mobile terminal device.
Adaptive array processing is a processing which calculates from a signal received from a mobile terminal device a weight vector formed of reception coefficients (weights) for respective antennas of the radio base station and provides adaptive control to accurately extract a signal received from a specific mobile terminal device.
The radio base station is provided with a reception weight vector calculator calculating such a weight vector for each symbol of a received signal and the calculator provides a processing to converge a weight vector to reduce a square of an error between a sum of complex multiplications of a received signal and a calculated weight vector, and a known reference signal, i.e., an adaptive array processing converging directivity of reception from a specific mobile terminal device.
In the adaptive array processing, such weight vector convergence is provided adaptively for example as time elapses and a signal's electric wave propagation path varies in characteristics, and a received signal has an interference component, noise and the like removed therefrom to extract a signal received from a specific mobile terminal device.
FIG. 17 is a functional block diagram for functionally illustrating an adaptive array processing performed in a radio base station's digital signal processor (DSP) by software.
With reference to FIG. 17, the radio base station has a plurality of antennas, for example four antennas A1–A4 receiving signals from mobile terminal device, respectively. The received signals undergo a variety of analog signal processing, as described hereinafter, in analog RF circuits 1–4 and are converted to digital signals by A/D converters 5–8, respectively.
These digital signals are fed to the radio base station's DSP and the FIG. 17 block diagram is then followed to provide the adaptive array processing by software.
With reference to FIG. 17, the received signals converted by A/D converters 5–8 to digital signals form a reception signal vector, which is in turn fed to multipliers M1–M4, respectively, each at one input, and also to reception weight vector calculator 11.
Reception weight vector calculator 11 uses an adaptive array algorithm described hereinafter to calculate a weight vector formed of weights for respective antennas and feeds the weights to multipliers M1–M4, respectively, each at the other input, to provide complex multiplications thereof by the vector of the signals received from the corresponding antennas. An adder 9 adds the complex multiplications together, which forms an array output signal.
The sum of the complex multiplications fed as the array output signal is also fed to reception weight vector calculator 11.
Reception weight vector calculator 11 receives a known reference signal d(t) previously stored in memory 10 and the signal is used in the calculation of a weight vector by the adaptive array algorithm. Reference signal d(t) is a known signal common to all users that is included in a signal received from a mobile terminal device, and for example for the PHS it is a section of the received signal that corresponds to a preamble (PR) and unique word (UW) configured of a known bit string.
Furthermore, reception weight vector calculator 11 receives the array output signal and the signal is used in the calculation of a weight vector by the adaptive array algorithm.
The reception weight vector calculator 11 employs Recursive Least Squares (RLS) algorithm, Sample Matrix Inversion (SMI) algorithm, or other similar adaptive array algorithm.
The RLS, SMI and other similar algorithms are a well known technique in the field of adaptive array processing, for example as specifically described by Nobuyoshi Kikuma, Adaptive Signal Processing by Array Antenna, Kagaku Gijutsu Shuppan, pp. 35–49, “Chapter 3 MMSE Adaptive Array.” Accordingly it will not be described.
Reference will now be made to FIG. 18, which is a schematic block diagram showing a specific configuration of analog RF circuit 1 shown in FIG. 17. Analog RF circuits 2–4 are identical in configuration to analog RF circuit 1 and accordingly will neither shown nor described.
With reference to FIG. 18, analog RF circuit 1 includes an amplifier 1a amplifying a radio frequency (RF) signal of an RF band received at antenna A1, a frequency mixer 1b using a local oscillation output received from a local oscillator (not shown) to convert in frequency the RF signal of the RF band to a baseband signal of a baseband, a bandpass filter BPF1c limiting an output of frequency converter 1c in bandwidth, and an amplifier 1d amplifying a baseband signal of a baseband output from BPF1c. 
Strictly, the RF signal of the RF band is initially converted by a first frequency mixer to an intermediate frequency (IF) signal of an IF band and then by a second frequency mixer to a baseband signal of a baseband. In FIG. 18, frequency mixer 1b represents such first and second frequency mixers collectively.
As can be seen from FIG. 18, analog RF circuits 1–4 are each configured of analog circuit components such as amplifiers 1a, 1d, frequency mixer 1b and filter 1c. However, because of variations in production, the analog RF circuits, configured of the same amplifiers, the same frequency mixer and the same filters, still provide different frequency characteristics of phase and amplitude and it is difficult to match the characteristics between the analog RF circuits.
Consequently, analog RF circuits 1–4 of signal streams corresponding to antennas A1–A4, respectively, would provide different frequency characteristics of phase and amplitude.
More specifically, if antennas A1–A4 receive the same signal, their respective analog RF circuits 1–4 having different frequency characteristics output signals having different waveforms. In other words, a waveform output through a frequency characteristic of each analog RF circuit has distortion relative to that output through an ideal characteristic.
That waveforms output from analog RF circuits 1–4, respectively, have distortion is equivalent to that there exists an interference component in an input signal for the adaptive array processing.
Signals of the streams of antennas A1–A4, respectively, having interference components therein from the outset would contribute to a significantly impaired ability of the radio base station employing an adaptive array to reduce the interference components.
An object of the present invention is therefore to provide a radio apparatus and its signal reception method and filter coefficient measurement method and program that can correct distortion in waveform of a received signal by compensating for an error of a characteristic between streams of received signals that results from an error of a characteristic of an analog circuit.
Another object of the present invention is to provide a radio apparatus and its signal reception method and filter coefficient measurement method and program that can provide an enhanced ability to reduce an interference component by adaptive array processing by compensating for an error of a characteristic between streams of received signals resulting from an error of a characteristic of an analog circuit, for each stream by means of a digital filter.